When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. pandas (software) - Wikipedia

    en.wikipedia.org/wiki/Pandas_(software)

    Pandas supports hierarchical indices with multiple values per data point. An index with this structure, called a "MultiIndex", allows a single DataFrame to represent multiple dimensions, similar to a pivot table in Microsoft Excel. [4]: 147–148 Each level of a MultiIndex can be given a unique name.

  3. Comma-separated values - Wikipedia

    en.wikipedia.org/wiki/Comma-separated_values

    Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record.

  4. Help:Introduction to tables with Wiki Markup/All - Wikipedia

    en.wikipedia.org/wiki/Help:Introduction_to...

    The two most commonly used classes are "wikitable" and "wikitable sortable"; the latter allows the reader to sort the table by clicking on the header cell of any column. caption Required for accessibility purposes on data tables, and placed only between the table start and the first table row.

  5. Table (database) - Wikipedia

    en.wikipedia.org/wiki/Table_(database)

    In a database, a table is a collection of related data organized in table format; consisting of columns and rows.. In relational databases, and flat file databases, a table is a set of data elements (values) using a model of vertical columns (identifiable by name) and horizontal rows, the cell being the unit where a row and column intersect. [1]

  6. Winsorizing - Wikipedia

    en.wikipedia.org/wiki/Winsorizing

    Note that winsorizing is not equivalent to simply excluding data, which is a simpler procedure, called trimming or truncation, but is a method of censoring data.. In a trimmed estimator, the extreme values are discarded; in a winsorized estimator, the extreme values are instead replaced by certain percentiles (the trimmed minimum and maximum).

  7. Latin hypercube sampling - Wikipedia

    en.wikipedia.org/wiki/Latin_hypercube_sampling

    In two dimensions the difference between random sampling, Latin hypercube sampling, and orthogonal sampling can be explained as follows: In random sampling new sample points are generated without taking into account the previously generated sample points. One does not necessarily need to know beforehand how many sample points are needed.

  8. Freedman–Diaconis rule - Wikipedia

    en.wikipedia.org/wiki/Freedman–Diaconis_rule

    This statistics -related article is a stub. You can help Wikipedia by expanding it.

  9. Heteroskedasticity-consistent standard errors - Wikipedia

    en.wikipedia.org/wiki/Heteroskedasticity...

    where is a k x 1 column vector of explanatory variables (features), is a k × 1 column vector of ...